Overview

Brought to you by YData

Dataset statistics

Number of variables23
Number of observations4803
Missing cells3941
Missing cells (%)3.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory863.2 KiB
Average record size in memory184.0 B

Variable types

Numeric9
Unsupported2
Text8
Categorical3
DateTime1

Alerts

budget is highly overall correlated with popularity and 3 other fieldsHigh correlation
label is highly overall correlated with vote_average and 1 other fieldsHigh correlation
popularity is highly overall correlated with budget and 3 other fieldsHigh correlation
popularity_scaled is highly overall correlated with budget and 3 other fieldsHigh correlation
revenue is highly overall correlated with budget and 3 other fieldsHigh correlation
vote_average is highly overall correlated with label and 1 other fieldsHigh correlation
vote_average_scaled is highly overall correlated with label and 1 other fieldsHigh correlation
vote_count is highly overall correlated with budget and 3 other fieldsHigh correlation
original_language is highly imbalanced (88.8%) Imbalance
status is highly imbalanced (98.8%) Imbalance
homepage has 3091 (64.4%) missing values Missing
tagline has 844 (17.6%) missing values Missing
id has unique values Unique
genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
spoken_languages is an unsupported type, check if it needs cleaning or further analysis Unsupported
budget has 1037 (21.6%) zeros Zeros
revenue has 1427 (29.7%) zeros Zeros
vote_average has 63 (1.3%) zeros Zeros
vote_count has 62 (1.3%) zeros Zeros
vote_average_scaled has 63 (1.3%) zeros Zeros

Reproduction

Analysis started2024-11-23 12:16:06.489137
Analysis finished2024-11-23 12:16:40.590814
Duration34.1 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

budget
Real number (ℝ)

High correlation  Zeros 

Distinct436
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29045040
Minimum0
Maximum3.8 × 108
Zeros1037
Zeros (%)21.6%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:40.891150image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1790000
median15000000
Q340000000
95-th percentile1.15 × 108
Maximum3.8 × 108
Range3.8 × 108
Interquartile range (IQR)39210000

Descriptive statistics

Standard deviation40722391
Coefficient of variation (CV)1.4020429
Kurtosis7.6580602
Mean29045040
Median Absolute Deviation (MAD)15000000
Skewness2.437211
Sum1.3950333 × 1011
Variance1.6583131 × 1015
MonotonicityNot monotonic
2024-11-23T12:16:41.273913image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1037
 
21.6%
20000000 144
 
3.0%
30000000 128
 
2.7%
25000000 126
 
2.6%
40000000 123
 
2.6%
15000000 120
 
2.5%
35000000 102
 
2.1%
50000000 101
 
2.1%
10000000 101
 
2.1%
60000000 86
 
1.8%
Other values (426) 2735
56.9%
ValueCountFrequency (%)
0 1037
21.6%
1 7
 
0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%
10 3
 
0.1%
11 1
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
380000000 1
 
< 0.1%
300000000 1
 
< 0.1%
280000000 1
 
< 0.1%
270000000 1
 
< 0.1%
260000000 2
 
< 0.1%
258000000 1
 
< 0.1%
255000000 1
 
< 0.1%
250000000 8
0.2%
245000000 1
 
< 0.1%
237000000 1
 
< 0.1%

genres
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size37.6 KiB

homepage
Text

Missing 

Distinct1691
Distinct (%)98.8%
Missing3091
Missing (%)64.4%
Memory size37.6 KiB
2024-11-23T12:16:41.654567image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length138
Median length80
Mean length36.419977
Min length17

Characters and Unicode

Total characters62351
Distinct characters78
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1677 ?
Unique (%)98.0%

Sample

1st rowhttp://www.avatarmovie.com/
2nd rowhttp://disney.go.com/disneypictures/pirates/
3rd rowhttp://www.sonypictures.com/movies/spectre/
4th rowhttp://www.thedarkknightrises.com/
5th rowhttp://movies.disney.com/john-carter
ValueCountFrequency (%)
http://www.missionimpossible.com 5
 
0.3%
http://www.transformersmovie.com 4
 
0.2%
http://www.thehungergames.movie 4
 
0.2%
http://www.thehobbit.com 3
 
0.2%
http://www.kungfupanda.com 3
 
0.2%
http://www.lordoftherings.net 3
 
0.2%
http://disney.go.com/disneypictures/pirates 2
 
0.1%
http://www.teenagemutantninjaturtlesmovie.com 2
 
0.1%
http://www.atlasshruggedmovie.com 2
 
0.1%
http://www.twilightthemovie.com 2
 
0.1%
Other values (1675) 1683
98.2%
2024-11-23T12:16:42.434353image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 5707
 
9.2%
/ 5701
 
9.1%
e 4467
 
7.2%
o 4438
 
7.1%
w 4418
 
7.1%
m 3492
 
5.6%
. 3393
 
5.4%
h 3110
 
5.0%
i 3017
 
4.8%
c 2543
 
4.1%
Other values (68) 22065
35.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 62351
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 5707
 
9.2%
/ 5701
 
9.1%
e 4467
 
7.2%
o 4438
 
7.1%
w 4418
 
7.1%
m 3492
 
5.6%
. 3393
 
5.4%
h 3110
 
5.0%
i 3017
 
4.8%
c 2543
 
4.1%
Other values (68) 22065
35.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 62351
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 5707
 
9.2%
/ 5701
 
9.1%
e 4467
 
7.2%
o 4438
 
7.1%
w 4418
 
7.1%
m 3492
 
5.6%
. 3393
 
5.4%
h 3110
 
5.0%
i 3017
 
4.8%
c 2543
 
4.1%
Other values (68) 22065
35.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 62351
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 5707
 
9.2%
/ 5701
 
9.1%
e 4467
 
7.2%
o 4438
 
7.1%
w 4418
 
7.1%
m 3492
 
5.6%
. 3393
 
5.4%
h 3110
 
5.0%
i 3017
 
4.8%
c 2543
 
4.1%
Other values (68) 22065
35.4%

id
Real number (ℝ)

Unique 

Distinct4803
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57165.484
Minimum5
Maximum459488
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:42.776285image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile578.1
Q19014.5
median14629
Q358610.5
95-th percentile285779
Maximum459488
Range459483
Interquartile range (IQR)49596

Descriptive statistics

Standard deviation88694.614
Coefficient of variation (CV)1.5515414
Kurtosis3.3467477
Mean57165.484
Median Absolute Deviation (MAD)12920
Skewness2.0720805
Sum2.7456582 × 108
Variance7.8667346 × 109
MonotonicityNot monotonic
2024-11-23T12:16:43.107282image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19995 1
 
< 0.1%
333355 1
 
< 0.1%
71157 1
 
< 0.1%
43418 1
 
< 0.1%
11588 1
 
< 0.1%
52010 1
 
< 0.1%
9671 1
 
< 0.1%
25968 1
 
< 0.1%
41248 1
 
< 0.1%
291081 1
 
< 0.1%
Other values (4793) 4793
99.8%
ValueCountFrequency (%)
5 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
16 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
22 1
< 0.1%
ValueCountFrequency (%)
459488 1
< 0.1%
447027 1
< 0.1%
433715 1
< 0.1%
426469 1
< 0.1%
426067 1
< 0.1%
417859 1
< 0.1%
408429 1
< 0.1%
407887 1
< 0.1%
402515 1
< 0.1%
396152 1
< 0.1%
Distinct4222
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:43.643002image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length3783
Median length749
Mean length277.01145
Min length2

Characters and Unicode

Total characters1330486
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4192 ?
Unique (%)87.3%

Sample

1st row[{"id": 1463, "name": "culture clash"}, {"id": 2964, "name": "future"}, {"id": 3386, "name": "space war"}, {"id": 3388, "name": "space colony"}, {"id": 3679, "name": "society"}, {"id": 3801, "name": "space travel"}, {"id": 9685, "name": "futuristic"}, {"id": 9840, "name": "romance"}, {"id": 9882, "name": "space"}, {"id": 9951, "name": "alien"}, {"id": 10148, "name": "tribe"}, {"id": 10158, "name": "alien planet"}, {"id": 10987, "name": "cgi"}, {"id": 11399, "name": "marine"}, {"id": 13065, "name": "soldier"}, {"id": 14643, "name": "battle"}, {"id": 14720, "name": "love affair"}, {"id": 165431, "name": "anti war"}, {"id": 193554, "name": "power relations"}, {"id": 206690, "name": "mind and soul"}, {"id": 209714, "name": "3d"}]
2nd row[{"id": 270, "name": "ocean"}, {"id": 726, "name": "drug abuse"}, {"id": 911, "name": "exotic island"}, {"id": 1319, "name": "east india trading company"}, {"id": 2038, "name": "love of one's life"}, {"id": 2052, "name": "traitor"}, {"id": 2580, "name": "shipwreck"}, {"id": 2660, "name": "strong woman"}, {"id": 3799, "name": "ship"}, {"id": 5740, "name": "alliance"}, {"id": 5941, "name": "calypso"}, {"id": 6155, "name": "afterlife"}, {"id": 6211, "name": "fighter"}, {"id": 12988, "name": "pirate"}, {"id": 157186, "name": "swashbuckler"}, {"id": 179430, "name": "aftercreditsstinger"}]
3rd row[{"id": 470, "name": "spy"}, {"id": 818, "name": "based on novel"}, {"id": 4289, "name": "secret agent"}, {"id": 9663, "name": "sequel"}, {"id": 14555, "name": "mi6"}, {"id": 156095, "name": "british secret service"}, {"id": 158431, "name": "united kingdom"}]
4th row[{"id": 849, "name": "dc comics"}, {"id": 853, "name": "crime fighter"}, {"id": 949, "name": "terrorist"}, {"id": 1308, "name": "secret identity"}, {"id": 1437, "name": "burglar"}, {"id": 3051, "name": "hostage drama"}, {"id": 3562, "name": "time bomb"}, {"id": 6969, "name": "gotham city"}, {"id": 7002, "name": "vigilante"}, {"id": 9665, "name": "cover-up"}, {"id": 9715, "name": "superhero"}, {"id": 9990, "name": "villainess"}, {"id": 10044, "name": "tragic hero"}, {"id": 13015, "name": "terrorism"}, {"id": 14796, "name": "destruction"}, {"id": 18933, "name": "catwoman"}, {"id": 156082, "name": "cat burglar"}, {"id": 156395, "name": "imax"}, {"id": 173272, "name": "flood"}, {"id": 179093, "name": "criminal underworld"}, {"id": 230775, "name": "batman"}]
5th row[{"id": 818, "name": "based on novel"}, {"id": 839, "name": "mars"}, {"id": 1456, "name": "medallion"}, {"id": 3801, "name": "space travel"}, {"id": 7376, "name": "princess"}, {"id": 9951, "name": "alien"}, {"id": 10028, "name": "steampunk"}, {"id": 10539, "name": "martian"}, {"id": 10685, "name": "escape"}, {"id": 161511, "name": "edgar rice burroughs"}, {"id": 163252, "name": "alien race"}, {"id": 179102, "name": "superhuman strength"}, {"id": 190320, "name": "mars civilization"}, {"id": 195446, "name": "sword and planet"}, {"id": 207928, "name": "19th century"}, {"id": 209714, "name": "3d"}]
ValueCountFrequency (%)
id 36196
22.1%
name 36195
22.1%
of 574
 
0.4%
on 565
 
0.3%
relationship 493
 
0.3%
based 486
 
0.3%
film 430
 
0.3%
429
 
0.3%
woman 413
 
0.3%
love 361
 
0.2%
Other values (17077) 87393
53.4%
2024-11-23T12:16:44.635298image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 217168
16.3%
158748
 
11.9%
e 74082
 
5.6%
: 72388
 
5.4%
, 68006
 
5.1%
i 66211
 
5.0%
a 65403
 
4.9%
n 61324
 
4.6%
d 49281
 
3.7%
m 47096
 
3.5%
Other values (44) 450779
33.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1330486
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
" 217168
16.3%
158748
 
11.9%
e 74082
 
5.6%
: 72388
 
5.4%
, 68006
 
5.1%
i 66211
 
5.0%
a 65403
 
4.9%
n 61324
 
4.6%
d 49281
 
3.7%
m 47096
 
3.5%
Other values (44) 450779
33.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1330486
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
" 217168
16.3%
158748
 
11.9%
e 74082
 
5.6%
: 72388
 
5.4%
, 68006
 
5.1%
i 66211
 
5.0%
a 65403
 
4.9%
n 61324
 
4.6%
d 49281
 
3.7%
m 47096
 
3.5%
Other values (44) 450779
33.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1330486
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
" 217168
16.3%
158748
 
11.9%
e 74082
 
5.6%
: 72388
 
5.4%
, 68006
 
5.1%
i 66211
 
5.0%
a 65403
 
4.9%
n 61324
 
4.6%
d 49281
 
3.7%
m 47096
 
3.5%
Other values (44) 450779
33.9%

original_language
Categorical

Imbalance 

Distinct37
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
en
4505 
fr
 
70
es
 
32
zh
 
27
de
 
27
Other values (32)
 
142

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters9606
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)0.3%

Sample

1st rowen
2nd rowen
3rd rowen
4th rowen
5th rowen

Common Values

ValueCountFrequency (%)
en 4505
93.8%
fr 70
 
1.5%
es 32
 
0.7%
zh 27
 
0.6%
de 27
 
0.6%
hi 19
 
0.4%
ja 16
 
0.3%
it 14
 
0.3%
cn 12
 
0.2%
ko 11
 
0.2%
Other values (27) 70
 
1.5%

Length

2024-11-23T12:16:44.983235image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
en 4505
93.8%
fr 70
 
1.5%
es 32
 
0.7%
zh 27
 
0.6%
de 27
 
0.6%
hi 19
 
0.4%
ja 16
 
0.3%
it 14
 
0.3%
cn 12
 
0.2%
ru 11
 
0.2%
Other values (27) 70
 
1.5%

Most occurring characters

ValueCountFrequency (%)
e 4569
47.6%
n 4523
47.1%
r 86
 
0.9%
f 75
 
0.8%
h 53
 
0.6%
s 42
 
0.4%
i 37
 
0.4%
d 36
 
0.4%
a 32
 
0.3%
t 30
 
0.3%
Other values (12) 123
 
1.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9606
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 4569
47.6%
n 4523
47.1%
r 86
 
0.9%
f 75
 
0.8%
h 53
 
0.6%
s 42
 
0.4%
i 37
 
0.4%
d 36
 
0.4%
a 32
 
0.3%
t 30
 
0.3%
Other values (12) 123
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9606
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 4569
47.6%
n 4523
47.1%
r 86
 
0.9%
f 75
 
0.8%
h 53
 
0.6%
s 42
 
0.4%
i 37
 
0.4%
d 36
 
0.4%
a 32
 
0.3%
t 30
 
0.3%
Other values (12) 123
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9606
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 4569
47.6%
n 4523
47.1%
r 86
 
0.9%
f 75
 
0.8%
h 53
 
0.6%
s 42
 
0.4%
i 37
 
0.4%
d 36
 
0.4%
a 32
 
0.3%
t 30
 
0.3%
Other values (12) 123
 
1.3%
Distinct4801
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:45.451638image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length86
Median length59
Mean length15.222986
Min length1

Characters and Unicode

Total characters73116
Distinct characters410
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4799 ?
Unique (%)99.9%

Sample

1st rowAvatar
2nd rowPirates of the Caribbean: At World's End
3rd rowSpectre
4th rowThe Dark Knight Rises
5th rowJohn Carter
ValueCountFrequency (%)
the 1420
 
10.7%
of 432
 
3.3%
a 168
 
1.3%
and 127
 
1.0%
in 110
 
0.8%
2 102
 
0.8%
to 102
 
0.8%
80
 
0.6%
man 65
 
0.5%
love 53
 
0.4%
Other values (5055) 10578
79.9%
2024-11-23T12:16:46.332417image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8436
 
11.5%
e 7412
 
10.1%
a 4625
 
6.3%
o 4370
 
6.0%
r 3892
 
5.3%
n 3885
 
5.3%
i 3723
 
5.1%
t 3600
 
4.9%
s 2857
 
3.9%
h 2717
 
3.7%
Other values (400) 27599
37.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 73116
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8436
 
11.5%
e 7412
 
10.1%
a 4625
 
6.3%
o 4370
 
6.0%
r 3892
 
5.3%
n 3885
 
5.3%
i 3723
 
5.1%
t 3600
 
4.9%
s 2857
 
3.9%
h 2717
 
3.7%
Other values (400) 27599
37.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 73116
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8436
 
11.5%
e 7412
 
10.1%
a 4625
 
6.3%
o 4370
 
6.0%
r 3892
 
5.3%
n 3885
 
5.3%
i 3723
 
5.1%
t 3600
 
4.9%
s 2857
 
3.9%
h 2717
 
3.7%
Other values (400) 27599
37.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 73116
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8436
 
11.5%
e 7412
 
10.1%
a 4625
 
6.3%
o 4370
 
6.0%
r 3892
 
5.3%
n 3885
 
5.3%
i 3723
 
5.1%
t 3600
 
4.9%
s 2857
 
3.9%
h 2717
 
3.7%
Other values (400) 27599
37.7%
Distinct4800
Distinct (%)100.0%
Missing3
Missing (%)0.1%
Memory size37.6 KiB
2024-11-23T12:16:46.815419image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length1000
Median length625
Mean length305.39875
Min length1

Characters and Unicode

Total characters1465914
Distinct characters127
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4800 ?
Unique (%)100.0%

Sample

1st rowIn the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.
2nd rowCaptain Barbossa, long believed to be dead, has come back to life and is headed to the edge of the Earth with Will Turner and Elizabeth Swann. But nothing is quite as it seems.
3rd rowA cryptic message from Bond’s past sends him on a trail to uncover a sinister organization. While M battles political forces to keep the secret service alive, Bond peels back the layers of deceit to reveal the terrible truth behind SPECTRE.
4th rowFollowing the death of District Attorney Harvey Dent, Batman assumes responsibility for Dent's crimes to protect the late attorney's reputation and is subsequently hunted by the Gotham City Police Department. Eight years later, Batman encounters the mysterious Selina Kyle and the villainous Bane, a new terrorist leader who overwhelms Gotham's finest. The Dark Knight resurfaces to protect a city that has branded him an enemy.
5th rowJohn Carter is a war-weary, former military captain who's inexplicably transported to the mysterious and exotic planet of Barsoom (Mars) and reluctantly becomes embroiled in an epic conflict. It's a world on the brink of collapse, and Carter rediscovers his humanity when he realizes the survival of Barsoom and its people rests in his hands.
ValueCountFrequency (%)
the 13894
 
5.5%
a 10452
 
4.2%
to 7925
 
3.2%
and 7388
 
3.0%
of 6867
 
2.7%
in 4536
 
1.8%
his 3994
 
1.6%
is 3369
 
1.3%
with 2533
 
1.0%
her 2163
 
0.9%
Other values (24224) 187234
74.8%
2024-11-23T12:16:47.671158image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
245712
16.8%
e 141178
 
9.6%
t 97104
 
6.6%
a 94907
 
6.5%
i 85329
 
5.8%
o 84373
 
5.8%
n 84015
 
5.7%
s 78343
 
5.3%
r 77154
 
5.3%
h 61948
 
4.2%
Other values (117) 415851
28.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1465914
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
245712
16.8%
e 141178
 
9.6%
t 97104
 
6.6%
a 94907
 
6.5%
i 85329
 
5.8%
o 84373
 
5.8%
n 84015
 
5.7%
s 78343
 
5.3%
r 77154
 
5.3%
h 61948
 
4.2%
Other values (117) 415851
28.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1465914
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
245712
16.8%
e 141178
 
9.6%
t 97104
 
6.6%
a 94907
 
6.5%
i 85329
 
5.8%
o 84373
 
5.8%
n 84015
 
5.7%
s 78343
 
5.3%
r 77154
 
5.3%
h 61948
 
4.2%
Other values (117) 415851
28.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1465914
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
245712
16.8%
e 141178
 
9.6%
t 97104
 
6.6%
a 94907
 
6.5%
i 85329
 
5.8%
o 84373
 
5.8%
n 84015
 
5.7%
s 78343
 
5.3%
r 77154
 
5.3%
h 61948
 
4.2%
Other values (117) 415851
28.4%

popularity
Real number (ℝ)

High correlation 

Distinct4802
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.492301
Minimum0
Maximum875.58131
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:48.016485image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3628167
Q14.66807
median12.921594
Q328.313505
95-th percentile67.385962
Maximum875.58131
Range875.58131
Interquartile range (IQR)23.645435

Descriptive statistics

Standard deviation31.81665
Coefficient of variation (CV)1.4803743
Kurtosis191.99582
Mean21.492301
Median Absolute Deviation (MAD)9.814445
Skewness9.7214159
Sum103227.52
Variance1012.2992
MonotonicityNot monotonic
2024-11-23T12:16:48.347259image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.902102 2
 
< 0.1%
150.437577 1
 
< 0.1%
7.247023 1
 
< 0.1%
14.038703 1
 
< 0.1%
3.949796 1
 
< 0.1%
3.789485 1
 
< 0.1%
3.891186 1
 
< 0.1%
16.072466 1
 
< 0.1%
4.799022 1
 
< 0.1%
2.351706 1
 
< 0.1%
Other values (4792) 4792
99.8%
ValueCountFrequency (%)
0 1
< 0.1%
0.000372 1
< 0.1%
0.001117 1
< 0.1%
0.001186 1
< 0.1%
0.001389 1
< 0.1%
0.001586 1
< 0.1%
0.002386 1
< 0.1%
0.002388 1
< 0.1%
0.003142 1
< 0.1%
0.003352 1
< 0.1%
ValueCountFrequency (%)
875.581305 1
< 0.1%
724.247784 1
< 0.1%
514.569956 1
< 0.1%
481.098624 1
< 0.1%
434.278564 1
< 0.1%
418.708552 1
< 0.1%
271.972889 1
< 0.1%
243.791743 1
< 0.1%
206.227151 1
< 0.1%
203.73459 1
< 0.1%
Distinct3697
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:48.966229image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length1155
Median length469
Mean length128.01499
Min length2

Characters and Unicode

Total characters614856
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3497 ?
Unique (%)72.8%

Sample

1st row[{"name": "Ingenious Film Partners", "id": 289}, {"name": "Twentieth Century Fox Film Corporation", "id": 306}, {"name": "Dune Entertainment", "id": 444}, {"name": "Lightstorm Entertainment", "id": 574}]
2nd row[{"name": "Walt Disney Pictures", "id": 2}, {"name": "Jerry Bruckheimer Films", "id": 130}, {"name": "Second Mate Productions", "id": 19936}]
3rd row[{"name": "Columbia Pictures", "id": 5}, {"name": "Danjaq", "id": 10761}, {"name": "B24", "id": 69434}]
4th row[{"name": "Legendary Pictures", "id": 923}, {"name": "Warner Bros.", "id": 6194}, {"name": "DC Entertainment", "id": 9993}, {"name": "Syncopy", "id": 9996}]
5th row[{"name": "Walt Disney Pictures", "id": 2}]
ValueCountFrequency (%)
name 13677
 
18.1%
id 13677
 
18.1%
pictures 2584
 
3.4%
films 1883
 
2.5%
productions 1830
 
2.4%
entertainment 1567
 
2.1%
film 915
 
1.2%
538
 
0.7%
corporation 404
 
0.5%
fox 372
 
0.5%
Other values (10124) 38291
50.6%
2024-11-23T12:16:50.277692image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 82064
 
13.3%
70935
 
11.5%
i 34526
 
5.6%
e 34198
 
5.6%
n 32605
 
5.3%
a 28315
 
4.6%
: 27355
 
4.4%
, 22976
 
3.7%
m 22254
 
3.6%
d 19878
 
3.2%
Other values (73) 239750
39.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 614856
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
" 82064
 
13.3%
70935
 
11.5%
i 34526
 
5.6%
e 34198
 
5.6%
n 32605
 
5.3%
a 28315
 
4.6%
: 27355
 
4.4%
, 22976
 
3.7%
m 22254
 
3.6%
d 19878
 
3.2%
Other values (73) 239750
39.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 614856
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
" 82064
 
13.3%
70935
 
11.5%
i 34526
 
5.6%
e 34198
 
5.6%
n 32605
 
5.3%
a 28315
 
4.6%
: 27355
 
4.4%
, 22976
 
3.7%
m 22254
 
3.6%
d 19878
 
3.2%
Other values (73) 239750
39.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 614856
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
" 82064
 
13.3%
70935
 
11.5%
i 34526
 
5.6%
e 34198
 
5.6%
n 32605
 
5.3%
a 28315
 
4.6%
: 27355
 
4.4%
, 22976
 
3.7%
m 22254
 
3.6%
d 19878
 
3.2%
Other values (73) 239750
39.0%
Distinct469
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:50.886144image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length517
Median length58
Mean length69.921299
Min length2

Characters and Unicode

Total characters335832
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique353 ?
Unique (%)7.3%

Sample

1st row[{"iso_3166_1": "US", "name": "United States of America"}, {"iso_3166_1": "GB", "name": "United Kingdom"}]
2nd row[{"iso_3166_1": "US", "name": "United States of America"}]
3rd row[{"iso_3166_1": "GB", "name": "United Kingdom"}, {"iso_3166_1": "US", "name": "United States of America"}]
4th row[{"iso_3166_1": "US", "name": "United States of America"}]
5th row[{"iso_3166_1": "US", "name": "United States of America"}]
ValueCountFrequency (%)
iso_3166_1 6436
16.7%
name 6436
16.7%
united 4606
11.9%
of 3956
10.2%
america 3956
10.2%
us 3956
10.2%
states 3956
10.2%
kingdom 636
 
1.6%
gb 636
 
1.6%
de 324
 
0.8%
Other values (180) 3698
9.6%
2024-11-23T12:16:52.181887image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 51488
 
15.3%
33793
 
10.1%
e 19992
 
6.0%
a 16820
 
5.0%
i 16187
 
4.8%
n 13165
 
3.9%
_ 12872
 
3.8%
1 12872
 
3.8%
6 12872
 
3.8%
: 12872
 
3.8%
Other values (51) 132899
39.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 335832
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
" 51488
 
15.3%
33793
 
10.1%
e 19992
 
6.0%
a 16820
 
5.0%
i 16187
 
4.8%
n 13165
 
3.9%
_ 12872
 
3.8%
1 12872
 
3.8%
6 12872
 
3.8%
: 12872
 
3.8%
Other values (51) 132899
39.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 335832
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
" 51488
 
15.3%
33793
 
10.1%
e 19992
 
6.0%
a 16820
 
5.0%
i 16187
 
4.8%
n 13165
 
3.9%
_ 12872
 
3.8%
1 12872
 
3.8%
6 12872
 
3.8%
: 12872
 
3.8%
Other values (51) 132899
39.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 335832
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
" 51488
 
15.3%
33793
 
10.1%
e 19992
 
6.0%
a 16820
 
5.0%
i 16187
 
4.8%
n 13165
 
3.9%
_ 12872
 
3.8%
1 12872
 
3.8%
6 12872
 
3.8%
: 12872
 
3.8%
Other values (51) 132899
39.6%
Distinct3280
Distinct (%)68.3%
Missing1
Missing (%)< 0.1%
Memory size37.6 KiB
Minimum1916-09-04 00:00:00
Maximum2017-02-03 00:00:00
2024-11-23T12:16:52.769532image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:53.567013image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

revenue
Real number (ℝ)

High correlation  Zeros 

Distinct3297
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82260639
Minimum0
Maximum2.7879651 × 109
Zeros1427
Zeros (%)29.7%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:53.881783image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median19170001
Q392917187
95-th percentile3.692849 × 108
Maximum2.7879651 × 109
Range2.7879651 × 109
Interquartile range (IQR)92917187

Descriptive statistics

Standard deviation1.628571 × 108
Coefficient of variation (CV)1.9797695
Kurtosis33.12363
Mean82260639
Median Absolute Deviation (MAD)19170001
Skewness4.4447164
Sum3.9509785 × 1011
Variance2.6522435 × 1016
MonotonicityNot monotonic
2024-11-23T12:16:54.203022image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1427
29.7%
7000000 6
 
0.1%
8000000 6
 
0.1%
6000000 5
 
0.1%
12000000 5
 
0.1%
10000000 5
 
0.1%
100000000 5
 
0.1%
14000000 4
 
0.1%
11000000 4
 
0.1%
5000000 4
 
0.1%
Other values (3287) 3332
69.4%
ValueCountFrequency (%)
0 1427
29.7%
5 1
 
< 0.1%
7 2
 
< 0.1%
10 1
 
< 0.1%
11 2
 
< 0.1%
12 2
 
< 0.1%
13 1
 
< 0.1%
14 1
 
< 0.1%
15 1
 
< 0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
2787965087 1
< 0.1%
1845034188 1
< 0.1%
1519557910 1
< 0.1%
1513528810 1
< 0.1%
1506249360 1
< 0.1%
1405403694 1
< 0.1%
1274219009 1
< 0.1%
1215439994 1
< 0.1%
1156730962 1
< 0.1%
1153304495 1
< 0.1%

runtime
Real number (ℝ)

Distinct156
Distinct (%)3.2%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean106.87586
Minimum0
Maximum338
Zeros35
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:54.538499image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile83
Q194
median103
Q3118
95-th percentile144
Maximum338
Range338
Interquartile range (IQR)24

Descriptive statistics

Standard deviation22.611935
Coefficient of variation (CV)0.21157196
Kurtosis8.9354488
Mean106.87586
Median Absolute Deviation (MAD)11
Skewness0.71595651
Sum513111
Variance511.29959
MonotonicityNot monotonic
2024-11-23T12:16:54.863106image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 163
 
3.4%
100 149
 
3.1%
98 140
 
2.9%
97 133
 
2.8%
95 123
 
2.6%
99 119
 
2.5%
94 116
 
2.4%
96 115
 
2.4%
101 114
 
2.4%
93 113
 
2.4%
Other values (146) 3516
73.2%
ValueCountFrequency (%)
0 35
0.7%
14 1
 
< 0.1%
25 1
 
< 0.1%
41 1
 
< 0.1%
42 1
 
< 0.1%
46 1
 
< 0.1%
47 1
 
< 0.1%
53 1
 
< 0.1%
59 1
 
< 0.1%
60 1
 
< 0.1%
ValueCountFrequency (%)
338 1
< 0.1%
276 1
< 0.1%
254 1
< 0.1%
248 1
< 0.1%
242 1
< 0.1%
240 1
< 0.1%
238 1
< 0.1%
229 1
< 0.1%
225 1
< 0.1%
219 1
< 0.1%

spoken_languages
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size37.6 KiB

status
Categorical

Imbalance 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
Released
4795 
Rumored
 
5
Post Production
 
3

Length

Max length15
Median length8
Mean length8.0033313
Min length7

Characters and Unicode

Total characters38440
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReleased
2nd rowReleased
3rd rowReleased
4th rowReleased
5th rowReleased

Common Values

ValueCountFrequency (%)
Released 4795
99.8%
Rumored 5
 
0.1%
Post Production 3
 
0.1%

Length

2024-11-23T12:16:55.194285image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-23T12:16:55.420546image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
released 4795
99.8%
rumored 5
 
0.1%
post 3
 
0.1%
production 3
 
0.1%

Most occurring characters

ValueCountFrequency (%)
e 14390
37.4%
d 4803
 
12.5%
R 4800
 
12.5%
s 4798
 
12.5%
l 4795
 
12.5%
a 4795
 
12.5%
o 14
 
< 0.1%
u 8
 
< 0.1%
r 8
 
< 0.1%
P 6
 
< 0.1%
Other values (6) 23
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38440
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 14390
37.4%
d 4803
 
12.5%
R 4800
 
12.5%
s 4798
 
12.5%
l 4795
 
12.5%
a 4795
 
12.5%
o 14
 
< 0.1%
u 8
 
< 0.1%
r 8
 
< 0.1%
P 6
 
< 0.1%
Other values (6) 23
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38440
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 14390
37.4%
d 4803
 
12.5%
R 4800
 
12.5%
s 4798
 
12.5%
l 4795
 
12.5%
a 4795
 
12.5%
o 14
 
< 0.1%
u 8
 
< 0.1%
r 8
 
< 0.1%
P 6
 
< 0.1%
Other values (6) 23
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38440
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 14390
37.4%
d 4803
 
12.5%
R 4800
 
12.5%
s 4798
 
12.5%
l 4795
 
12.5%
a 4795
 
12.5%
o 14
 
< 0.1%
u 8
 
< 0.1%
r 8
 
< 0.1%
P 6
 
< 0.1%
Other values (6) 23
 
0.1%

tagline
Text

Missing 

Distinct3944
Distinct (%)99.6%
Missing844
Missing (%)17.6%
Memory size37.6 KiB
2024-11-23T12:16:55.894518image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length252
Median length149
Mean length41.988886
Min length3

Characters and Unicode

Total characters166234
Distinct characters92
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3930 ?
Unique (%)99.3%

Sample

1st rowEnter the World of Pandora.
2nd rowAt the end of the world, the adventure begins.
3rd rowA Plan No One Escapes
4th rowThe Legend Ends
5th rowLost in our world, found in another.
ValueCountFrequency (%)
the 1880
 
6.1%
a 1085
 
3.5%
to 705
 
2.3%
is 653
 
2.1%
of 620
 
2.0%
you 535
 
1.7%
in 443
 
1.4%
and 328
 
1.1%
for 323
 
1.0%
it 310
 
1.0%
Other values (4349) 23980
77.7%
2024-11-23T12:16:56.799693image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26926
16.2%
e 17450
 
10.5%
o 10463
 
6.3%
t 10358
 
6.2%
a 8761
 
5.3%
n 8406
 
5.1%
i 8137
 
4.9%
r 7933
 
4.8%
s 7648
 
4.6%
h 6587
 
4.0%
Other values (82) 53565
32.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 166234
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
26926
16.2%
e 17450
 
10.5%
o 10463
 
6.3%
t 10358
 
6.2%
a 8761
 
5.3%
n 8406
 
5.1%
i 8137
 
4.9%
r 7933
 
4.8%
s 7648
 
4.6%
h 6587
 
4.0%
Other values (82) 53565
32.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 166234
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
26926
16.2%
e 17450
 
10.5%
o 10463
 
6.3%
t 10358
 
6.2%
a 8761
 
5.3%
n 8406
 
5.1%
i 8137
 
4.9%
r 7933
 
4.8%
s 7648
 
4.6%
h 6587
 
4.0%
Other values (82) 53565
32.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 166234
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
26926
16.2%
e 17450
 
10.5%
o 10463
 
6.3%
t 10358
 
6.2%
a 8761
 
5.3%
n 8406
 
5.1%
i 8137
 
4.9%
r 7933
 
4.8%
s 7648
 
4.6%
h 6587
 
4.0%
Other values (82) 53565
32.2%

title
Text

Distinct4800
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:57.356430image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length86
Median length58
Mean length15.349157
Min length1

Characters and Unicode

Total characters73722
Distinct characters98
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4797 ?
Unique (%)99.9%

Sample

1st rowAvatar
2nd rowPirates of the Caribbean: At World's End
3rd rowSpectre
4th rowThe Dark Knight Rises
5th rowJohn Carter
ValueCountFrequency (%)
the 1526
 
11.4%
of 474
 
3.5%
a 180
 
1.3%
and 139
 
1.0%
in 116
 
0.9%
to 107
 
0.8%
2 103
 
0.8%
79
 
0.6%
man 66
 
0.5%
love 56
 
0.4%
Other values (4810) 10508
78.7%
2024-11-23T12:16:58.288643image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8553
 
11.6%
e 7525
 
10.2%
a 4632
 
6.3%
o 4470
 
6.1%
n 3950
 
5.4%
r 3946
 
5.4%
i 3765
 
5.1%
t 3660
 
5.0%
s 2862
 
3.9%
h 2852
 
3.9%
Other values (88) 27507
37.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 73722
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8553
 
11.6%
e 7525
 
10.2%
a 4632
 
6.3%
o 4470
 
6.1%
n 3950
 
5.4%
r 3946
 
5.4%
i 3765
 
5.1%
t 3660
 
5.0%
s 2862
 
3.9%
h 2852
 
3.9%
Other values (88) 27507
37.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 73722
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8553
 
11.6%
e 7525
 
10.2%
a 4632
 
6.3%
o 4470
 
6.1%
n 3950
 
5.4%
r 3946
 
5.4%
i 3765
 
5.1%
t 3660
 
5.0%
s 2862
 
3.9%
h 2852
 
3.9%
Other values (88) 27507
37.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 73722
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8553
 
11.6%
e 7525
 
10.2%
a 4632
 
6.3%
o 4470
 
6.1%
n 3950
 
5.4%
r 3946
 
5.4%
i 3765
 
5.1%
t 3660
 
5.0%
s 2862
 
3.9%
h 2852
 
3.9%
Other values (88) 27507
37.3%

vote_average
Real number (ℝ)

High correlation  Zeros 

Distinct71
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0921716
Minimum0
Maximum10
Zeros63
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:58.667316image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.3
Q15.6
median6.2
Q36.8
95-th percentile7.6
Maximum10
Range10
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation1.1946122
Coefficient of variation (CV)0.19608971
Kurtosis7.7923628
Mean6.0921716
Median Absolute Deviation (MAD)0.6
Skewness-1.95971
Sum29260.7
Variance1.4270982
MonotonicityNot monotonic
2024-11-23T12:16:59.003565image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.5 216
 
4.5%
6 216
 
4.5%
6.7 213
 
4.4%
6.3 207
 
4.3%
6.1 201
 
4.2%
6.4 201
 
4.2%
6.2 200
 
4.2%
6.6 198
 
4.1%
5.9 196
 
4.1%
5.8 187
 
3.9%
Other values (61) 2768
57.6%
ValueCountFrequency (%)
0 63
1.3%
0.5 1
 
< 0.1%
1 2
 
< 0.1%
1.9 1
 
< 0.1%
2 6
 
0.1%
2.2 1
 
< 0.1%
2.3 2
 
< 0.1%
2.4 1
 
< 0.1%
2.6 1
 
< 0.1%
2.7 1
 
< 0.1%
ValueCountFrequency (%)
10 4
 
0.1%
9.5 1
 
< 0.1%
9.3 1
 
< 0.1%
8.5 2
 
< 0.1%
8.4 2
 
< 0.1%
8.3 7
 
0.1%
8.2 15
0.3%
8.1 18
0.4%
8 35
0.7%
7.9 32
0.7%

vote_count
Real number (ℝ)

High correlation  Zeros 

Distinct1609
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean690.21799
Minimum0
Maximum13752
Zeros62
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:59.298822image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q154
median235
Q3737
95-th percentile3040.9
Maximum13752
Range13752
Interquartile range (IQR)683

Descriptive statistics

Standard deviation1234.5859
Coefficient of variation (CV)1.7886898
Kurtosis19.913946
Mean690.21799
Median Absolute Deviation (MAD)214
Skewness3.8240685
Sum3315117
Variance1524202.3
MonotonicityNot monotonic
2024-11-23T12:16:59.617264image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 62
 
1.3%
1 53
 
1.1%
2 46
 
1.0%
4 43
 
0.9%
3 41
 
0.9%
6 38
 
0.8%
8 37
 
0.8%
10 34
 
0.7%
11 32
 
0.7%
9 32
 
0.7%
Other values (1599) 4385
91.3%
ValueCountFrequency (%)
0 62
1.3%
1 53
1.1%
2 46
1.0%
3 41
0.9%
4 43
0.9%
5 28
0.6%
6 38
0.8%
7 31
0.6%
8 37
0.8%
9 32
0.7%
ValueCountFrequency (%)
13752 1
< 0.1%
12002 1
< 0.1%
11800 1
< 0.1%
11776 1
< 0.1%
10995 1
< 0.1%
10867 1
< 0.1%
10099 1
< 0.1%
9742 1
< 0.1%
9455 1
< 0.1%
9427 1
< 0.1%

vote_average_scaled
Real number (ℝ)

High correlation  Zeros 

Distinct71
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.60921716
Minimum0
Maximum1
Zeros63
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2024-11-23T12:16:59.979803image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.43
Q10.56
median0.62
Q30.68
95-th percentile0.76
Maximum1
Range1
Interquartile range (IQR)0.12

Descriptive statistics

Standard deviation0.11946122
Coefficient of variation (CV)0.19608971
Kurtosis7.7923628
Mean0.60921716
Median Absolute Deviation (MAD)0.06
Skewness-1.95971
Sum2926.07
Variance0.014270982
MonotonicityNot monotonic
2024-11-23T12:17:00.302957image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.65 216
 
4.5%
0.6 216
 
4.5%
0.67 213
 
4.4%
0.63 207
 
4.3%
0.61 201
 
4.2%
0.64 201
 
4.2%
0.62 200
 
4.2%
0.66 198
 
4.1%
0.59 196
 
4.1%
0.58 187
 
3.9%
Other values (61) 2768
57.6%
ValueCountFrequency (%)
0 63
1.3%
0.05 1
 
< 0.1%
0.1 2
 
< 0.1%
0.19 1
 
< 0.1%
0.2 6
 
0.1%
0.22 1
 
< 0.1%
0.23 2
 
< 0.1%
0.24 1
 
< 0.1%
0.26 1
 
< 0.1%
0.27 1
 
< 0.1%
ValueCountFrequency (%)
1 4
 
0.1%
0.95 1
 
< 0.1%
0.93 1
 
< 0.1%
0.85 2
 
< 0.1%
0.84 2
 
< 0.1%
0.83 7
 
0.1%
0.82 15
0.3%
0.81 18
0.4%
0.8 35
0.7%
0.79 32
0.7%

popularity_scaled
Real number (ℝ)

High correlation 

Distinct4802
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.024546322
Minimum0
Maximum1
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2024-11-23T12:17:00.620023image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00041437237
Q10.0053313952
median0.014757732
Q30.032336808
95-th percentile0.076961399
Maximum1
Range1
Interquartile range (IQR)0.027005413

Descriptive statistics

Standard deviation0.036337744
Coefficient of variation (CV)1.4803743
Kurtosis191.99582
Mean0.024546322
Median Absolute Deviation (MAD)0.011209062
Skewness9.7214159
Sum117.89598
Variance0.0013204317
MonotonicityNot monotonic
2024-11-23T12:17:00.963062image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01016707637 2
 
< 0.1%
0.1718145147 1
 
< 0.1%
0.008276813311 1
 
< 0.1%
0.01603358011 1
 
< 0.1%
0.004511055658 1
 
< 0.1%
0.004327964723 1
 
< 0.1%
0.004444117271 1
 
< 0.1%
0.01835633756 1
 
< 0.1%
0.005480955307 1
 
< 0.1%
0.00268587964 1
 
< 0.1%
Other values (4792) 4792
99.8%
ValueCountFrequency (%)
0 1
< 0.1%
4.248606016 × 10-71
< 0.1%
1.275723903 × 10-61
< 0.1%
1.354528692 × 10-61
< 0.1%
1.586374666 × 10-61
< 0.1%
1.811368049 × 10-61
< 0.1%
2.725046762 × 10-61
< 0.1%
2.727330959 × 10-61
< 0.1%
3.588473146 × 10-61
< 0.1%
3.828313808 × 10-61
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
0.8271622291 1
< 0.1%
0.587689519 1
< 0.1%
0.5494619646 1
< 0.1%
0.4959888494 1
< 0.1%
0.4782063637 1
< 0.1%
0.310619799 1
< 0.1%
0.2784341575 1
< 0.1%
0.2355316974 1
< 0.1%
0.2326849475 1
< 0.1%

label
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
1
2555 
0
2248 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4803
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
1 2555
53.2%
0 2248
46.8%

Length

2024-11-23T12:17:01.248425image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-23T12:17:01.454067image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
1 2555
53.2%
0 2248
46.8%

Most occurring characters

ValueCountFrequency (%)
1 2555
53.2%
0 2248
46.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4803
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 2555
53.2%
0 2248
46.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4803
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 2555
53.2%
0 2248
46.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4803
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 2555
53.2%
0 2248
46.8%

Interactions

2024-11-23T12:16:36.093892image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:12.200347image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:16.856932image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:21.604932image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:24.178902image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:26.306986image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:28.725161image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:30.899589image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:33.124087image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:36.411132image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:12.631723image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:17.276778image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:21.968401image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:24.420417image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:26.548143image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:28.973742image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:31.155321image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:33.497192image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:36.694787image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:13.145617image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:19.375460image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:22.314934image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:24.647610image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:26.798374image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:29.185018image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:31.391928image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:33.798968image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:37.033516image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:13.620301image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:19.670150image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:22.651057image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:24.884090image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:27.017806image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:29.407146image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:31.607248image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:34.089411image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:37.366387image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:14.054558image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:20.005708image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:23.027586image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:25.115427image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:27.274389image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:29.622191image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:31.881587image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:34.379938image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:38.062314image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:14.620477image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:20.330373image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:23.270316image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:25.361783image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:27.747223image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:29.880399image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:32.116398image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:34.736975image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:38.418936image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:15.276949image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:20.634089image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:23.486226image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:25.583152image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:27.997344image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:30.119867image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:32.348954image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:35.057933image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:38.665274image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:15.716424image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:21.028079image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:23.717772image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:25.841461image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:28.254293image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:30.385077image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:32.604168image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:35.371037image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:38.922087image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:16.256075image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:21.291726image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:23.939778image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:26.066003image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:28.492589image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:30.605367image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:32.853829image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-23T12:16:35.733047image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Correlations

2024-11-23T12:17:01.619281image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
budgetidlabeloriginal_languagepopularitypopularity_scaledrevenueruntimestatusvote_averagevote_average_scaledvote_count
budget1.000-0.2460.0500.0000.6490.6490.7570.3260.0000.0660.0660.663
id-0.2461.0000.1120.089-0.278-0.278-0.292-0.2160.048-0.266-0.266-0.297
label0.0500.1121.0000.0890.0990.0990.1400.3050.0000.9210.9210.238
original_language0.0000.0890.0891.0000.0000.0000.0000.0200.2750.0590.0590.000
popularity0.649-0.2780.0990.0001.0001.0000.7770.3020.0000.3590.3590.960
popularity_scaled0.649-0.2780.0990.0001.0001.0000.7770.3020.0000.3590.3590.960
revenue0.757-0.2920.1400.0000.7770.7771.0000.3170.0000.2430.2430.804
runtime0.326-0.2160.3050.0200.3020.3020.3171.0000.0290.3980.3980.304
status0.0000.0480.0000.2750.0000.0000.0000.0291.0000.1310.1310.000
vote_average0.066-0.2660.9210.0590.3590.3590.2430.3980.1311.0001.0000.381
vote_average_scaled0.066-0.2660.9210.0590.3590.3590.2430.3980.1311.0001.0000.381
vote_count0.663-0.2970.2380.0000.9600.9600.8040.3040.0000.3810.3811.000

Missing values

2024-11-23T12:16:39.299081image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-23T12:16:40.003781image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-11-23T12:16:40.416546image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

budgetgenreshomepageidkeywordsoriginal_languageoriginal_titleoverviewpopularityproduction_companiesproduction_countriesrelease_daterevenueruntimespoken_languagesstatustaglinetitlevote_averagevote_countvote_average_scaledpopularity_scaledlabel
0237000000[Action, Adventure, Fantasy, Science Fiction]http://www.avatarmovie.com/19995[{"id": 1463, "name": "culture clash"}, {"id": 2964, "name": "future"}, {"id": 3386, "name": "space war"}, {"id": 3388, "name": "space colony"}, {"id": 3679, "name": "society"}, {"id": 3801, "name": "space travel"}, {"id": 9685, "name": "futuristic"}, {"id": 9840, "name": "romance"}, {"id": 9882, "name": "space"}, {"id": 9951, "name": "alien"}, {"id": 10148, "name": "tribe"}, {"id": 10158, "name": "alien planet"}, {"id": 10987, "name": "cgi"}, {"id": 11399, "name": "marine"}, {"id": 13065, "name": "soldier"}, {"id": 14643, "name": "battle"}, {"id": 14720, "name": "love affair"}, {"id": 165431, "name": "anti war"}, {"id": 193554, "name": "power relations"}, {"id": 206690, "name": "mind and soul"}, {"id": 209714, "name": "3d"}]enAvatarIn the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.150.437577[{"name": "Ingenious Film Partners", "id": 289}, {"name": "Twentieth Century Fox Film Corporation", "id": 306}, {"name": "Dune Entertainment", "id": 444}, {"name": "Lightstorm Entertainment", "id": 574}][{"iso_3166_1": "US", "name": "United States of America"}, {"iso_3166_1": "GB", "name": "United Kingdom"}]2009-12-102787965087162.0[English, Español]ReleasedEnter the World of Pandora.Avatar7.2118000.720.1718151
1300000000[Adventure, Fantasy, Action]http://disney.go.com/disneypictures/pirates/285[{"id": 270, "name": "ocean"}, {"id": 726, "name": "drug abuse"}, {"id": 911, "name": "exotic island"}, {"id": 1319, "name": "east india trading company"}, {"id": 2038, "name": "love of one's life"}, {"id": 2052, "name": "traitor"}, {"id": 2580, "name": "shipwreck"}, {"id": 2660, "name": "strong woman"}, {"id": 3799, "name": "ship"}, {"id": 5740, "name": "alliance"}, {"id": 5941, "name": "calypso"}, {"id": 6155, "name": "afterlife"}, {"id": 6211, "name": "fighter"}, {"id": 12988, "name": "pirate"}, {"id": 157186, "name": "swashbuckler"}, {"id": 179430, "name": "aftercreditsstinger"}]enPirates of the Caribbean: At World's EndCaptain Barbossa, long believed to be dead, has come back to life and is headed to the edge of the Earth with Will Turner and Elizabeth Swann. But nothing is quite as it seems.139.082615[{"name": "Walt Disney Pictures", "id": 2}, {"name": "Jerry Bruckheimer Films", "id": 130}, {"name": "Second Mate Productions", "id": 19936}][{"iso_3166_1": "US", "name": "United States of America"}]2007-05-19961000000169.0[English]ReleasedAt the end of the world, the adventure begins.Pirates of the Caribbean: At World's End6.945000.690.1588461
2245000000[Action, Adventure, Crime]http://www.sonypictures.com/movies/spectre/206647[{"id": 470, "name": "spy"}, {"id": 818, "name": "based on novel"}, {"id": 4289, "name": "secret agent"}, {"id": 9663, "name": "sequel"}, {"id": 14555, "name": "mi6"}, {"id": 156095, "name": "british secret service"}, {"id": 158431, "name": "united kingdom"}]enSpectreA cryptic message from Bond’s past sends him on a trail to uncover a sinister organization. While M battles political forces to keep the secret service alive, Bond peels back the layers of deceit to reveal the terrible truth behind SPECTRE.107.376788[{"name": "Columbia Pictures", "id": 5}, {"name": "Danjaq", "id": 10761}, {"name": "B24", "id": 69434}][{"iso_3166_1": "GB", "name": "United Kingdom"}, {"iso_3166_1": "US", "name": "United States of America"}]2015-10-26880674609148.0[Français, English, Español, Italiano, Deutsch]ReleasedA Plan No One EscapesSpectre6.344660.630.1226351
3250000000[Action, Crime, Drama, Thriller]http://www.thedarkknightrises.com/49026[{"id": 849, "name": "dc comics"}, {"id": 853, "name": "crime fighter"}, {"id": 949, "name": "terrorist"}, {"id": 1308, "name": "secret identity"}, {"id": 1437, "name": "burglar"}, {"id": 3051, "name": "hostage drama"}, {"id": 3562, "name": "time bomb"}, {"id": 6969, "name": "gotham city"}, {"id": 7002, "name": "vigilante"}, {"id": 9665, "name": "cover-up"}, {"id": 9715, "name": "superhero"}, {"id": 9990, "name": "villainess"}, {"id": 10044, "name": "tragic hero"}, {"id": 13015, "name": "terrorism"}, {"id": 14796, "name": "destruction"}, {"id": 18933, "name": "catwoman"}, {"id": 156082, "name": "cat burglar"}, {"id": 156395, "name": "imax"}, {"id": 173272, "name": "flood"}, {"id": 179093, "name": "criminal underworld"}, {"id": 230775, "name": "batman"}]enThe Dark Knight RisesFollowing the death of District Attorney Harvey Dent, Batman assumes responsibility for Dent's crimes to protect the late attorney's reputation and is subsequently hunted by the Gotham City Police Department. Eight years later, Batman encounters the mysterious Selina Kyle and the villainous Bane, a new terrorist leader who overwhelms Gotham's finest. The Dark Knight resurfaces to protect a city that has branded him an enemy.112.312950[{"name": "Legendary Pictures", "id": 923}, {"name": "Warner Bros.", "id": 6194}, {"name": "DC Entertainment", "id": 9993}, {"name": "Syncopy", "id": 9996}][{"iso_3166_1": "US", "name": "United States of America"}]2012-07-161084939099165.0[English]ReleasedThe Legend EndsThe Dark Knight Rises7.691060.760.1282721
4260000000[Action, Adventure, Science Fiction]http://movies.disney.com/john-carter49529[{"id": 818, "name": "based on novel"}, {"id": 839, "name": "mars"}, {"id": 1456, "name": "medallion"}, {"id": 3801, "name": "space travel"}, {"id": 7376, "name": "princess"}, {"id": 9951, "name": "alien"}, {"id": 10028, "name": "steampunk"}, {"id": 10539, "name": "martian"}, {"id": 10685, "name": "escape"}, {"id": 161511, "name": "edgar rice burroughs"}, {"id": 163252, "name": "alien race"}, {"id": 179102, "name": "superhuman strength"}, {"id": 190320, "name": "mars civilization"}, {"id": 195446, "name": "sword and planet"}, {"id": 207928, "name": "19th century"}, {"id": 209714, "name": "3d"}]enJohn CarterJohn Carter is a war-weary, former military captain who's inexplicably transported to the mysterious and exotic planet of Barsoom (Mars) and reluctantly becomes embroiled in an epic conflict. It's a world on the brink of collapse, and Carter rediscovers his humanity when he realizes the survival of Barsoom and its people rests in his hands.43.926995[{"name": "Walt Disney Pictures", "id": 2}][{"iso_3166_1": "US", "name": "United States of America"}]2012-03-07284139100132.0[English]ReleasedLost in our world, found in another.John Carter6.121240.610.0501690
5258000000[Fantasy, Action, Adventure]http://www.sonypictures.com/movies/spider-man3/559[{"id": 851, "name": "dual identity"}, {"id": 1453, "name": "amnesia"}, {"id": 1965, "name": "sandstorm"}, {"id": 2038, "name": "love of one's life"}, {"id": 3446, "name": "forgiveness"}, {"id": 3986, "name": "spider"}, {"id": 4391, "name": "wretch"}, {"id": 4959, "name": "death of a friend"}, {"id": 5776, "name": "egomania"}, {"id": 5789, "name": "sand"}, {"id": 5857, "name": "narcism"}, {"id": 6062, "name": "hostility"}, {"id": 8828, "name": "marvel comic"}, {"id": 9663, "name": "sequel"}, {"id": 9715, "name": "superhero"}, {"id": 9748, "name": "revenge"}]enSpider-Man 3The seemingly invincible Spider-Man goes up against an all-new crop of villain – including the shape-shifting Sandman. While Spider-Man’s superpowers are altered by an alien organism, his alter ego, Peter Parker, deals with nemesis Eddie Brock and also gets caught up in a love triangle.115.699814[{"name": "Columbia Pictures", "id": 5}, {"name": "Laura Ziskin Productions", "id": 326}, {"name": "Marvel Enterprises", "id": 19551}][{"iso_3166_1": "US", "name": "United States of America"}]2007-05-01890871626139.0[English, Français]ReleasedThe battle within.Spider-Man 35.935760.590.1321410
6260000000[Animation, Family]http://disney.go.com/disneypictures/tangled/38757[{"id": 1562, "name": "hostage"}, {"id": 2343, "name": "magic"}, {"id": 2673, "name": "horse"}, {"id": 3205, "name": "fairy tale"}, {"id": 4344, "name": "musical"}, {"id": 7376, "name": "princess"}, {"id": 10336, "name": "animation"}, {"id": 33787, "name": "tower"}, {"id": 155658, "name": "blonde woman"}, {"id": 162219, "name": "selfishness"}, {"id": 163545, "name": "healing power"}, {"id": 179411, "name": "based on fairy tale"}, {"id": 179431, "name": "duringcreditsstinger"}, {"id": 215258, "name": "healing gift"}, {"id": 234183, "name": "animal sidekick"}]enTangledWhen the kingdom's most wanted-and most charming-bandit Flynn Rider hides out in a mysterious tower, he's taken hostage by Rapunzel, a beautiful and feisty tower-bound teen with 70 feet of magical, golden hair. Flynn's curious captor, who's looking for her ticket out of the tower where she's been locked away for years, strikes a deal with the handsome thief and the unlikely duo sets off on an action-packed escapade, complete with a super-cop horse, an over-protective chameleon and a gruff gang of pub thugs.48.681969[{"name": "Walt Disney Pictures", "id": 2}, {"name": "Walt Disney Animation Studios", "id": 6125}][{"iso_3166_1": "US", "name": "United States of America"}]2010-11-24591794936100.0[English]ReleasedThey're taking adventure to new lengths.Tangled7.433300.740.0556001
7280000000[Action, Adventure, Science Fiction]http://marvel.com/movies/movie/193/avengers_age_of_ultron99861[{"id": 8828, "name": "marvel comic"}, {"id": 9663, "name": "sequel"}, {"id": 9715, "name": "superhero"}, {"id": 9717, "name": "based on comic book"}, {"id": 10629, "name": "vision"}, {"id": 155030, "name": "superhero team"}, {"id": 179431, "name": "duringcreditsstinger"}, {"id": 180547, "name": "marvel cinematic universe"}, {"id": 209714, "name": "3d"}]enAvengers: Age of UltronWhen Tony Stark tries to jumpstart a dormant peacekeeping program, things go awry and Earth’s Mightiest Heroes are put to the ultimate test as the fate of the planet hangs in the balance. As the villainous Ultron emerges, it is up to The Avengers to stop him from enacting his terrible plans, and soon uneasy alliances and unexpected action pave the way for an epic and unique global adventure.134.279229[{"name": "Marvel Studios", "id": 420}, {"name": "Prime Focus", "id": 15357}, {"name": "Revolution Sun Studios", "id": 76043}][{"iso_3166_1": "US", "name": "United States of America"}]2015-04-221405403694141.0[English]ReleasedA New Age Has Come.Avengers: Age of Ultron7.367670.730.1533601
8250000000[Adventure, Fantasy, Family]http://harrypotter.warnerbros.com/harrypotterandthehalf-bloodprince/dvd/index.html767[{"id": 616, "name": "witch"}, {"id": 2343, "name": "magic"}, {"id": 3872, "name": "broom"}, {"id": 3884, "name": "school of witchcraft"}, {"id": 6333, "name": "wizardry"}, {"id": 10164, "name": "apparition"}, {"id": 10791, "name": "teenage crush"}, {"id": 12564, "name": "werewolf"}]enHarry Potter and the Half-Blood PrinceAs Harry begins his sixth year at Hogwarts, he discovers an old book marked as 'Property of the Half-Blood Prince', and begins to learn more about Lord Voldemort's dark past.98.885637[{"name": "Warner Bros.", "id": 6194}, {"name": "Heyday Films", "id": 7364}][{"iso_3166_1": "GB", "name": "United Kingdom"}, {"iso_3166_1": "US", "name": "United States of America"}]2009-07-07933959197153.0[English]ReleasedDark Secrets RevealedHarry Potter and the Half-Blood Prince7.452930.740.1129371
9250000000[Action, Adventure, Fantasy]http://www.batmanvsupermandawnofjustice.com/209112[{"id": 849, "name": "dc comics"}, {"id": 7002, "name": "vigilante"}, {"id": 9715, "name": "superhero"}, {"id": 9717, "name": "based on comic book"}, {"id": 9748, "name": "revenge"}, {"id": 163455, "name": "super powers"}, {"id": 195242, "name": "clark kent"}, {"id": 195243, "name": "bruce wayne"}, {"id": 229266, "name": "dc extended universe"}]enBatman v Superman: Dawn of JusticeFearing the actions of a god-like Super Hero left unchecked, Gotham City’s own formidable, forceful vigilante takes on Metropolis’s most revered, modern-day savior, while the world wrestles with what sort of hero it really needs. And with Batman and Superman at war with one another, a new threat quickly arises, putting mankind in greater danger than it’s ever known before.155.790452[{"name": "DC Comics", "id": 429}, {"name": "Atlas Entertainment", "id": 507}, {"name": "Warner Bros.", "id": 6194}, {"name": "DC Entertainment", "id": 9993}, {"name": "Cruel & Unusual Films", "id": 9995}, {"name": "RatPac-Dune Entertainment", "id": 41624}][{"iso_3166_1": "US", "name": "United States of America"}]2016-03-23873260194151.0[English]ReleasedJustice or revengeBatman v Superman: Dawn of Justice5.770040.570.1779280
budgetgenreshomepageidkeywordsoriginal_languageoriginal_titleoverviewpopularityproduction_companiesproduction_countriesrelease_daterevenueruntimespoken_languagesstatustaglinetitlevote_averagevote_countvote_average_scaledpopularity_scaledlabel
47930[Drama]NaN182291[{"id": 718, "name": "confession"}, {"id": 10079, "name": "hazing"}, {"id": 33426, "name": "gang member"}, {"id": 33586, "name": "latino"}, {"id": 158718, "name": "lgbt"}, {"id": 172391, "name": "catholic priest"}, {"id": 196374, "name": "shakespeare's romeo and juliet"}, {"id": 208340, "name": "latino lgbt"}, {"id": 209241, "name": "gang initiation"}, {"id": 209242, "name": "gunplay"}]enOn The DownlowIsaac and Angel are two young Latinos involved in a south side Chicago gang. They have a secret in a world where secrets are forbidden.0.029757[{"name": "Iconoclast Films", "id": 26677}][{"iso_3166_1": "US", "name": "United States of America"}]2004-04-11090.0[]ReleasedTwo gangs. One secret. One crossroad.On The Downlow6.020.600.0000340
47940[Thriller, Horror, Comedy]NaN286939[]enSanctuary: Quite a ConundrumIt should have been just a normal day of sex, fun, alcohol, hormones and debauchery for Tabitha and Mimi, two over-privileged twenty-somethings. But that so-called normalcy gets tossed out the window when a devastating event occurs at a pool party.0.166513[{"name": "Gold Lion Films", "id": 37870}, {"name": "T-Street Productions", "id": 37871}][{"iso_3166_1": "US", "name": "United States of America"}]2012-01-20082.0[English]ReleasedNaNSanctuary: Quite a Conundrum0.000.000.0001900
47950[Drama]NaN124606[{"id": 10726, "name": "gang"}, {"id": 33928, "name": "audition"}, {"id": 172732, "name": "police fake"}, {"id": 177927, "name": "homeless"}, {"id": 207583, "name": "actress"}]enBangA young woman in L.A. is having a bad day: she's evicted, an audition ends with a producer furious she won't trade sex for the part, and a policeman nabs her for something she didn't do, demanding fellatio to release her. She snaps, grabs his gun, takes his uniform, and leaves him cuffed to a tree where he's soon having a defenseless chat with a homeless man. She takes off on the cop's motorcycle and, for an afternoon, experiences a cop's life. She talks a young man out of suicide and then is plunged into violence after a friendly encounter with two "vatos." She is torn between self-protection and others' expectations. Is there any resolution for her torrent of feelings?0.918116[{"name": "Asylum Films", "id": 10571}, {"name": "FM Entertainment", "id": 26598}, {"name": "Eagle Eye Films Inc.", "id": 40739}][{"iso_3166_1": "US", "name": "United States of America"}]1995-09-09098.0[English]ReleasedSometimes you've got to break the rulesBang6.010.600.0010490
47967000[Science Fiction, Drama, Thriller]http://www.primermovie.com14337[{"id": 1448, "name": "distrust"}, {"id": 2101, "name": "garage"}, {"id": 3394, "name": "identity crisis"}, {"id": 4379, "name": "time travel"}, {"id": 5455, "name": "time machine"}, {"id": 6009, "name": "mathematics"}, {"id": 10183, "name": "independent film"}, {"id": 14779, "name": "paradox"}, {"id": 162356, "name": "mechanical engineering"}]enPrimerFriends/fledgling entrepreneurs invent a device in their garage that reduces the apparent mass of any object placed inside it, but they accidentally discover that it has some highly unexpected capabilities -- ones that could enable them to do and to have seemingly anything they want. Taking advantage of this unique opportunity is the first challenge they face. Dealing with the consequences is the next.23.307949[{"name": "Thinkfilm", "id": 446}][{"iso_3166_1": "US", "name": "United States of America"}]2004-10-0842476077.0[English]ReleasedWhat happens if it actually works?Primer6.96580.690.0266201
47970[Foreign, Thriller]NaN67238[]enCaviteAdam, a security guard, travels from California to the Philippines, his native land, for his father's funeral. He arrives in Manila. As he waits, a phone rings in his backpack; he answers it, and a male voice tells him that his mother and sister are captives and will be killed if Adam doesn't cooperate. Over the next hour, the voice sends Adam by bus, taxi, motorized tricycle, and on foot through an urban landscape of busy streets, cramped apartments, a fetid squatters' camp, a bank, a cockfighting arena, and a church. Adam's conversations with the voice cover murder, Islam, jihad, rebellion in Mindanao, and his family. What is it Adam will be commanded to do?0.022173[][]2005-03-12080.0[]ReleasedNaNCavite7.520.750.0000251
4798220000[Action, Crime, Thriller]NaN9367[{"id": 5616, "name": "united states\u2013mexico barrier"}, {"id": 33649, "name": "legs"}, {"id": 162740, "name": "arms"}, {"id": 187891, "name": "paper knife"}, {"id": 206558, "name": "guitar case"}]esEl MariachiEl Mariachi just wants to play his guitar and carry on the family tradition. Unfortunately, the town he tries to find work in has another visitor...a killer who carries his guns in a guitar case. The drug lord and his henchmen mistake El Mariachi for the killer, Azul, and chase him around town trying to kill him and get his guitar case.14.269792[{"name": "Columbia Pictures", "id": 5}][{"iso_3166_1": "MX", "name": "Mexico"}, {"iso_3166_1": "US", "name": "United States of America"}]1992-09-04204092081.0[Español]ReleasedHe didn't come looking for trouble, but trouble came looking for him.El Mariachi6.62380.660.0162981
47999000[Comedy, Romance]NaN72766[]enNewlywedsA newlywed couple's honeymoon is upended by the arrivals of their respective sisters.0.642552[][]2011-12-26085.0[]ReleasedA newlywed couple's honeymoon is upended by the arrivals of their respective sisters.Newlyweds5.950.590.0007340
48000[Comedy, Drama, Romance, TV Movie]http://www.hallmarkchannel.com/signedsealeddelivered231617[{"id": 248, "name": "date"}, {"id": 699, "name": "love at first sight"}, {"id": 2398, "name": "narration"}, {"id": 5340, "name": "investigation"}, {"id": 34051, "name": "team"}, {"id": 173066, "name": "postal worker"}]enSigned, Sealed, Delivered"Signed, Sealed, Delivered" introduces a dedicated quartet of civil servants in the Dead Letter Office of the U.S. Postal System who transform themselves into an elite team of lost-mail detectives. Their determination to deliver the seemingly undeliverable takes them out of the post office into an unpredictable world where letters and packages from the past save lives, solve crimes, reunite old loves, and change futures by arriving late, but always miraculously on time.1.444476[{"name": "Front Street Pictures", "id": 3958}, {"name": "Muse Entertainment Enterprises", "id": 6438}][{"iso_3166_1": "US", "name": "United States of America"}]2013-10-130120.0[English]ReleasedNaNSigned, Sealed, Delivered7.060.700.0016501
48010[]http://shanghaicalling.com/126186[]enShanghai CallingWhen ambitious New York attorney Sam is sent to Shanghai on assignment, he immediately stumbles into a legal mess that could end his career. With the help of a beautiful relocation specialist, a well-connected old-timer, a clever journalist, and a street-smart legal assistant, Sam might just save his job, find romance, and learn to appreciate the beauty and wonders of Shanghai. Written by Anonymous (IMDB.com).0.857008[][{"iso_3166_1": "US", "name": "United States of America"}, {"iso_3166_1": "CN", "name": "China"}]2012-05-03098.0[English]ReleasedA New Yorker in ShanghaiShanghai Calling5.770.570.0009790
48020[Documentary]NaN25975[{"id": 1523, "name": "obsession"}, {"id": 2249, "name": "camcorder"}, {"id": 9986, "name": "crush"}, {"id": 11223, "name": "dream girl"}]enMy Date with DrewEver since the second grade when he first saw her in E.T. The Extraterrestrial, Brian Herzlinger has had a crush on Drew Barrymore. Now, 20 years later he's decided to try to fulfill his lifelong dream by asking her for a date. There's one small problem: She's Drew Barrymore and he's, well, Brian Herzlinger, a broke 27-year-old aspiring filmmaker from New Jersey.1.929883[{"name": "rusty bear entertainment", "id": 87986}, {"name": "lucky crow films", "id": 87987}][{"iso_3166_1": "US", "name": "United States of America"}]2005-08-05090.0[English]ReleasedNaNMy Date with Drew6.3160.630.0022041